 
@article{arbel20,
  title={KALE: When Energy-Based Learning Meets Adversarial Training},
  author={Michal Arbel and Liang Zhou and Arthur Gretton},
  journal={ArXiv},
  year={2020},
  volume={abs/2003.05033}
}

@book{rao,
  author={C. R. Rao and H. Toutenburg and Shalabh and C. Heumann},
  title={Linear Models and Generalizations},
  publisher={Springer-Verlag},
  address={Berlin},
  year=1995
}

@book{shao,
  author={J. Shao},
  title={Mathematical Statistics},
  publisher={Springer},
  address={New York},
  year=2003
}


@book{demidenko,
  author={Demidenko E.},
  title={Mixed models: theory and applications with R},
  publisher={John Wiley & Sons},
  address={New Jersey},
  year=2013
}

@article{demidenko,
  author={Harrison X. A. and Donaldson L. and Correa-Cano M. E. and Evans J. and Fisher D. N. and Goodwin C. E. D. and Robinson B. S. and Hodgson D. J. and Inger R.},
  title={A brief introduction to mixed effects modelling and multi-model inference in ecology},
  url={https://doi.org/10.7717/peerj.4794},
  journal={PeerJ},
  volume=6,
  year=2018
}

@article{song22a,
  title={基于PyMC的线性混合模型及其在印染工业上的应用},
  author={宋丛威 and 张晓明},
  journal={电子技术与软件工程},
  year=2022,
  volume=30,
  number=4,
  pages={37-40},
  note="The Linear Mixed Models Based on PyMC and Its Application in Printing and Dyeing Industry"
}

@article{song22b,
  title={增量Bayes线性回归算法的构造与工业应用},
  author={宋丛威 and 张晓明},
  journal={计算机应用研究},
  year=2022,
  pages={100-102+107},
}


吴密霞. 线性混合效应模型引论. 北京：北京工业大学, 2020.

@article{tarpey,
  title={A Note on the Prediction Sum of Squares Statistic for Restricted Least Squares},
  author={Tarpey T.},
  journal={The American Statistician},
  year=2000,
  volume=54,
  number=2,
  pages={116-118},
  url={https://doi.org/10.2307/2686028}
}

@article{tarpey,
  title={The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation},
  author={Chicco D. and Warrens M. J. and Jurman G.},
  journal={PeerJ Comput Sci.},
  year=2021,
  volume=7,
  doi={10.7717/peerj-cs.623}
}


% Ordinary Least Squares. http://www.statsmodels.org/stable/regression.html.

@article{tibshirani,
  title={Regression Shrinkage and Selection via the lasso. Journal of the Royal Statistical Society},
  author={Tibshirani R.},
  journal={Wiley},
  year=1996,
  volume=58,
  number=1,
  pages={267–288}
}

Andrew W. Lo, Ruixun Zhang, The evolutionary origin of Bayesian heuristics and finite memory, iScience, 2021, 24(8) https://doi.org/10.1016/j.isci.2021.102853.
